A Multi-Flow Production Line for Sorting of Eggs Using Image Processing.
Fatih AkkoyunAdem OzcelikIbrahim ArpaciAli ErcetinSinan GucluerPublished in: Sensors (Basel, Switzerland) (2022)
In egg production facilities, the classification of eggs is carried out either manually or by using sophisticated systems such as load cells. However, there is a need for the classification of eggs to be carried out with faster and cheaper methods. In the agri-food industry, the use of image processing technology is continuously increasing due to the data processing speed and cost-effective solutions. In this study, an image processing approach was used to classify chicken eggs on an industrial roller conveyor line in real-time. A color camera was used to acquire images in an illumination cabinet on a motorized roller conveyor while eggs are moving on the movement halls. The system successfully operated for the grading of eggs in the industrial multi-flow production line in real-time. There were significant correlations among measured weights of the eggs after image processing. The coefficient of linear correlation (R 2 ) between measured and actual weights was 0.95.
Keyphrases
- deep learning
- convolutional neural network
- machine learning
- heavy metals
- artificial intelligence
- wastewater treatment
- induced apoptosis
- magnetic resonance imaging
- computed tomography
- signaling pathway
- risk assessment
- mass spectrometry
- magnetic resonance
- electronic health record
- oxidative stress
- cell cycle arrest
- climate change
- contrast enhanced